Technical data analyst skills for the digital business
by Kamalika Some
July 26, 2020
Data, often seen as a powerful tool for business transformation, will force companies to seek out resources capable of understanding the dynamics of this powerful resource to interpret the trends hidden within them. Data analysts have great potential to influence business decisions. If we are talking about Analytics, it is broken down into three components, which include the business context, data science, and technology motivators. Data science, a vast study in itself, brings together a wide range of expertise, including statistical and operations research, machine learning, and deep learning algorithms.
Speaking of data science professionals, data analysts are the ones who start early in this profession. If you’re wondering what the skills of a good data science analyst are, read the Best Data Analyst Skills for the Digital Business.
Excel for basic analysis
Data analysts need to understand Excel, which is a popular data analysis tool. To understand basic data analysis and data visualization, Excel provides two-dimensional tables, complex nested tables, pie charts, radar charts, combo charts, line charts, column charts, bar charts , area charts, scatter charts, etc. Additionally, users can use pivot tables. , and complex functions like Vlookup to process hundreds of thousands of data.
Data warehousing know-how
Data analysts need to know the source and storage of their data, as well as the basics of data pipelines. Data warehousing encapsulates the systems for creating and organizing virtual storage for a company’s data. Data warehouses are often managed by project managers and data analysts who consistently monitor data, for safeguarding and compliance with data privacy laws.
SQL for data recovery
SQL or Structured Query Language is often considered the industry standard database language and is often considered a higher version of Excel; SQL can handle large sets of data that Excel simply cannot.
Excel skills are required by almost any organization to manage and store data, link multiple databases, or make changes to existing database structures. Even non-technical professionals can benefit from learning SQL, and if you’re looking to work in big data, learning SQL is a must.
Programming and coding skills
Programming and coding skills are a must for any data analyst, without knowledge of programming languages ââthey will not be able to put their knowledge into practice. Popular programming languages ââused by as many companies as possible include R, SAS, and Python. Knowledge of coding languages ââhelps a data analyst perform advanced analyzes on complex data sets without relying on data scientists for the task. an expert in extension programming.
Communicate with data visualization
Data analysts need communication skills to be able to communicate the history of data to management. Data visualization skills which include expertise in the table, QlikView can have a decisive effect in decoding the data. Data visualization tools like PowerBI, D3.js, and HighCharts have their unique advantages. Data analysts should be proficient in at least one visualization tool.
AI and machine learning
Artificial intelligence and advanced machine learning capabilities are something every data analytics professional should know about. Knowledge of model building, mathematical optimization, and logical deduction would help data analysts be at the forefront of data science to understand industry trends.
In the future, knowing what skills data analysts will need to advance their careers is dynamic. Technologies evolve and the need to break into analytics and start working with data silos is a must. Industries are buzzing about Big Data, and companies are looking for knowledgeable data science professionals who can help them with data-centric strategic planning. Crucially, improving your data analysis skills and knowledge means more opportunities for you in the post-COVID-19 future.
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